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Information Technology Journal

Year: 2009 | Volume: 8 | Issue: 4 | Page No.: 476-485
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Authors

Guiyi Wei

Haiping Liu

Mande Xie

Keywords

Research Article

Clustering Large Spatial Data with Local-density and its Application

Guiyi Wei, Haiping Liu and Mande Xie
In this study, a new algorithm LD-BSCA is proposed with introducing the concept of local MinPts (a minimum number of points) and the new cluster expanding condition: ExpandConClId (Expanding Condition of ClId-th Cluster). We minimize the algorithm input down to only one parameter and let the local MinPts diversified as clusters change from one to another simultaneously. Experiments show LD-BSCA algorithm is powerful to discover all clusters in gradient distributing databases. In addition, we introduce an efficient searching method to reduce the runtime of present algorithm. Using several databases, we demonstrate the high quality of the proposed algorithm in clustering the implicit knowledge in asymmetric distribution databases.
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Ashish Sharma Reply

This is Ashish Sharma want to read this paper please send immediately.

Ashish Sharma Reply

This is Ashish Sharma want to read this paper please send this paper to my mail id.

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